---
title: "Dashboard"
output: 
  flexdashboard::flex_dashboard:
    orientation: columns
    vertical_layout: fill
    source: embed
---

```{r setup, include=FALSE}
library(flexdashboard)
library(plotly)
library(p8105.datasets)
library(dplyr)
```

```{r}
# Load the NY NOAA data
data("ny_noaa")
df <- ny_noaa

# Filtering for complete cases for tmax and tmin, and limiting to 5000 rows for performance
df <- df %>%
  filter(!is.na(tmax) & !is.na(tmin) & !is.na(prcp)) %>%
  mutate(year = as.numeric(format(date, "%Y")),
         month = as.numeric(format(date, "%m"))) %>%
  sample_n(5000)
```

Column {data-width=650}
-----------------------------------------------------------------------

### Chart A

```{r}
# Ensure tmax and tmin are numeric
df$tmax <- as.numeric(df$tmax)
df$tmin <- as.numeric(df$tmin)

# Scatter plot of tmax vs tmin
plot_ly(data = df, x = ~tmin, y = ~tmax, type = "scatter", mode = "markers",
        marker = list(color = 'blue', opacity = 0.5)) %>%
  layout(title = "Scatter Plot of Maximum vs Minimum Temperature",
         xaxis = list(title = "Minimum Temperature (°C)", type = "linear"),
         yaxis = list(title = "Maximum Temperature (°C)", type = "linear"))
```

Column {data-width=350}
-----------------------------------------------------------------------

### Chart B

```{r}
# Calculate average precipitation for each month across all years
monthly_avg_precip <- df %>%
  group_by(month) %>%
  summarise(avg_precip = mean(prcp, na.rm = TRUE), .groups = "drop") %>%
  arrange(month)

# Create a bar plot
plot_ly(data = monthly_avg_precip, 
        x = ~factor(month, levels = 1:12, labels = month.abb), 
        y = ~avg_precip, 
        type = "bar",
        marker = list(color = ~avg_precip, colorscale = "Blues"), 
        text = ~round(avg_precip, 2), 
        textposition = 'outside') %>% 
  layout(title = list(text = "Average Precipitation by Month (All Years)", font = list(size = 24)),
         xaxis = list(title = "Month", tickfont = list(size = 14)),
         yaxis = list(title = "Average Precipitation (mm)", tickfont = list(size = 14)),
         margin = list(t = 60), 
         showlegend = FALSE)
```

### Chart C

```{r}
# Calculate monthly average maximum temperature over the years
monthly_temp <- df %>%
  group_by(year, month) %>%
  summarise(mean_tmax = mean(tmax, na.rm = TRUE), .groups = "drop") %>%
  arrange(year, month)

# Create the line plot
plot_ly(data = monthly_temp, 
        x = ~year, 
        y = ~mean_tmax, 
        color = ~factor(month, labels = month.abb), # Color each month distinctly
        type = "scatter", 
        mode = "lines") %>%
  layout(title = "Monthly Average Maximum Temperature Over Years",
         xaxis = list(title = "Year"),
         yaxis = list(title = "Average Maximum Temperature (°C)"),
         legend = list(title = list(text = "Month")))
```